Folyamatkinyerés

Folyamatkinyerés, a Hungarian term, translates to "process mining" in English. It is a data science discipline that focuses on analyzing and understanding business processes based on event logs. These event logs are digital records generated by information systems, capturing activities performed by users or systems within a specific process. By mining these logs, process mining aims to discover, monitor, and improve real-world business processes.

The core idea behind process mining is to move beyond subjective assumptions about how processes are executed and instead rely on objective data. It employs algorithms to reconstruct the actual flow of activities, identifying variations, bottlenecks, and deviations from the intended or declared process. This allows organizations to gain a factual understanding of their operational efficiency and effectiveness.

Key objectives of process mining include process discovery, which automatically generates a process model from event logs; process conformance checking, which compares the executed process with a predefined model to identify deviations; and process enhancement, which uses insights from discovery and conformance to optimize and improve processes. The insights derived from process mining can lead to significant improvements in areas such as operational efficiency, cost reduction, compliance, and customer satisfaction. It is a powerful tool for digital transformation and operational excellence.